{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 双y轴绘制及合并图例\n",
    "### 双y轴绘制 关键函数：twinx()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# -*- coding: utf-8 -*-\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import rc\n",
    "%matplotlib inline\n",
    "\n",
    "rc('mathtext', default='regular')\n",
    "\n",
    "time = np.arange(10)\n",
    "temp = np.random.random(10)*30\n",
    "Swdown = np.random.random(10)*100-10\n",
    "Rn = np.random.random(10)*100-10\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "ax.plot(time, Swdown, '-', label = 'Swdown')\n",
    "ax.plot(time, Rn, '-', label = 'Rn')\n",
    "ax2 = ax.twinx()\n",
    "ax2.plot(time, temp, '-r', label = 'temp')\n",
    "ax.legend(loc=2)\n",
    "ax.grid()\n",
    "ax.set_xlabel(\"Time (h)\")\n",
    "ax.set_ylabel(r\"Radiation ($MJ\\,m^{-2}\\,d^{-1}$)\")\n",
    "ax2.set_ylabel(r\"Temperature ($^\\circ$C)\")\n",
    "ax2.set_ylim(0, 35)\n",
    "ax.set_ylim(-20,100)\n",
    "ax2.legend(loc=0)\n",
    "plt.savefig('0.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 合并图例\n",
    "### 仅使用一个轴的legend()函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rc('mathtext', default='regular')\n",
    "\n",
    "time = np.arange(10)\n",
    "temp = np.random.random(10)*30\n",
    "Swdown = np.random.random(10)*100-10\n",
    "Rn = np.random.random(10)*100-10\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "\n",
    "lns1 = ax.plot(time, Swdown, '-', label = 'Swdown')\n",
    "lns2 = ax.plot(time, Rn, '-', label = 'Rn')\n",
    "ax2 = ax.twinx()\n",
    "lns3 = ax2.plot(time, temp, '-r', label = 'temp')\n",
    "\n",
    "# added these three lines\n",
    "lns = lns1+lns2+lns3\n",
    "labs = [l.get_label() for l in lns]\n",
    "ax.legend(lns, labs, loc=0)\n",
    "\n",
    "ax.grid()\n",
    "ax.set_xlabel(\"Time (h)\")\n",
    "ax.set_ylabel(r\"Radiation ($MJ\\,m^{-2}\\,d^{-1}$)\")\n",
    "ax2.set_ylabel(r\"Temperature ($^\\circ$C)\")\n",
    "ax2.set_ylim(0, 35)\n",
    "ax.set_ylim(-20,100)\n",
    "plt.savefig('0.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 使用figure.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(0,10)\n",
    "y = np.linspace(0,10)\n",
    "z = np.sin(x/3)**2*98\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "ax.plot(x,y, '-', label = 'Quantity 1')\n",
    "\n",
    "ax2 = ax.twinx()\n",
    "ax2.plot(x,z, '-r', label = 'Quantity 2')\n",
    "fig.legend(loc=1, bbox_to_anchor=(1,1), bbox_transform=ax.transAxes)\n",
    "\n",
    "ax.set_xlabel(\"x [units]\")\n",
    "ax.set_ylabel(r\"Quantity 1\")\n",
    "ax2.set_ylabel(r\"Quantity 2\")\n",
    "\n",
    "plt.savefig('0.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## matplotlib绘制多个图形单独显示"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#创建自变量数组\n",
    "x= np.linspace(0,2*np.pi,500)\n",
    "#创建函数值数组\n",
    "y1 = np.sin(x)\n",
    "y2 = np.cos(x)\n",
    "y3 = np.sin(x*x)\n",
    "#创建图形\n",
    "plt.figure(1)\n",
    "'''\n",
    "意思是在一个2行2列共4个子图的图中，定位第1个图来进行操作（画图）。\n",
    "最后面那个1表示第1个子图。那个数字的变化来定位不同的子图\n",
    "'''\n",
    "#第一行第一列图形\n",
    "ax1 = plt.subplot(2,2,1)\n",
    "#第一行第二列图形\n",
    "ax2 = plt.subplot(2,2,2)\n",
    "#第二行\n",
    "ax3 = plt.subplot(2,1,2)\n",
    "#选择ax1\n",
    "plt.sca(ax1)\n",
    "#绘制红色曲线\n",
    "plt.plot(x,y1,color='red')\n",
    "#限制y坐标轴范围\n",
    "plt.ylim(-1.2,1.2)\n",
    "#选择ax2\n",
    "plt.sca(ax2)\n",
    "#绘制蓝色曲线\n",
    "plt.plot(x,y2,'b--')\n",
    "plt.ylim(-1.2,1.2)\n",
    "#选择ax3\n",
    "plt.sca(ax3)\n",
    "plt.plot(x,y3,'g--')\n",
    "plt.ylim(-1.2,1.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## figure图的嵌套"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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wVq5ciZUrVwIAEhMT0bFjR0RHR+Pxxx/HX/7yF63DNy97P6Q5c9zXD0mYgyf3Q9KKl9Y4eM0cQ2FhIXr27In4+Hg8+uijuPPOO2udB7hSx44d8c0339S4f/z48ZVfExGWL1+uabw+QfohCVd4ej8krdhrHEaOVDUO777r8RPsXnPGMH/+fOTk5GDcuHFYs2YNOnXqhFmzZuHo0aNGh+a7pB+ScJa39EPSipddx8FrEgOgPtm3bdsWbdu2hZ+fH3755Rfcd999mD59utGh+R7phyRc4U39kLQyc6aqa1iwAKhl2bwn8ZrEsHTpUiQkJGD69Ono06cPvvvuO6xYsQL79u3Dpk2bjA7PeGVlwLffuu940g9JOMsb+yFpwYtqHLwmMZw+fRqbN2/Gxx9/jPvvvx9NbGOSjRo1wtatWw2OzkDMwL/+BXTvDsTGAkuW6H9M6YcknOXN/ZC0YK9xiI1VNQ4e2pfNaxLDvHnzEBkZWetjMTExbo7GQ3z/PXDnncCwYUDjxsAdd6g/1v/U8XpI0g9JuMLeD+m117yzH5IWvKDGwWsSg6ji9Gl1KhobC2Rnq6rRb78FPvxQFZglJwN79+pzbHs/pFdekX5IomHM0g9JCx5e4yCJwZuUlakx/ehoNXk1YYKqOn7ySbXcr1kzNazUrh1w991q7bSWpB+ScIVZ+iFpxYNrHCQxeIOq8whTpwI33wx89516g4WEVN+2VSs1qcWsPomcPq1dHPZ+SEuXSj8k0TBm64ekFQ+9joO8uz3dlfMI6enqFPRq8yo33KCGlfLz1fMuXHA9DumHJJxl1n5IWvHAGgdJDJ6qrnkER2sGbrlFXfBk717g4YeBigrX4pkyRfohCeeYuR+SVjysxkESg6epbx6hIZKSgIULgc2bgWnTnI8pIwPYtk36IYmG84V+SFrwsBoHr+mVZHrM6pPV00+rRDB4sKoKdXUp7lNPqStKLVqkrig1eXLDni/9kIQrfKUfkhY86DoOcsbgCaxW4JFHGjaP4CgilWDuvde5GoelS6UfknCOr/VD0oKH1DhIYvAEM2cC69YBf/5zw+YRHNW4sZpvaGiNQ2GhWmIo/ZCEM3yxH5IWPKDGwfSJIT8/H7fddhtiYmLQrVs3LKmlZcSuXbsQHByMuLg4xMXFYd68ee4LcPlyVQU6caJqSqfX6faVNQ6OdKWVfkjCWb7aD0krRtc4MLPH3BISElhrJ06c4H379jEzc3FxMXfq1IkPHjxYbZudO3fy0KFDG7RfTWLdsoW5USPmYcOYL192fX+OOHyYOSSEuVMn5qKiurfLzGQGmKdPd09cOtPjd0vUoaKCOSGBOTycuaTE6Gi82/r16n2YnMxstbq8OwDZ7MDfYl3PGIioBRGlEdGPRHSIiG7W83i1CQsLQ7xtAicwMBAxMTEoKChwdxg1ffUV8Ic/ABYLsGGDGu5xB3uNQ16eGvutrcZB+iEJV0g/JO0YVOOg91DSEgAfMXMXALEADul8vKvKzc3F119/jV69etV4bM+ePYiNjcWQIUNw8OBBfQP56SfgrrvUH95//UsN87iTvcZhzx7V2sJqrf649EMSzpJ+SNozosbBkdMKZ24AggD8LwBy9Dl6nu6XlJRwfHw8b9q0qcZj586d4xLbKe+2bds4Ojq61n389a9/5YSEBE5ISOAOHTo4F8jp08ydOzNfdx3zjz86tw+tvPGGOk2dOvW3+4qLmdu2Ze7VSw0JmIQMJbnJ1KnMRMy24VuhkfJy5sRE5saNmT/91OndwMGhJD0TQxyALABrAHwNYBWA5rVslwIgG0C2039s61FWVsaDBg3ihQsXOrR9ZGQkF11t/J2d/ENz4QJz377M117L/PnnDX++1qxW5kmT1K/BkiXqvunT1feZmcbGpjFJDG7www/Mfn7Mjz9udCTmVFLCPHMm86+/Or0LT0gMFgCXAfSyfb8EwItXe44eb16r1cqjRo3iyZMn17nNyZMn2Wqb2MnMzOT27dtXfl+XBsdaUcH8wAPqv/z99xv2XD1dvsx8773qU97rrzM3acI8ZozRUWlOEoPOrFbmO+9kDg5mPnXK6GhEHRxNDHpWPh8HcJyZM23fpwGYqePxarV7926sW7cON954I+Li4gAACxYsQF5eHgBg/PjxSEtLw4oVK+Dn5wd/f39s3LgRpHVb4JkzgfffB15/Hbj/fm337Qp7jcPttwPPPKPmFKQfkmgoez+kRYukH5IJ6JYYmLmQiPKJqDMzHwZwB4Af9DpeXfr27Ws/g6nTxIkTMXHiRP2CsNcqTJig2mZ7GnuNQ1KS6p4q/ZBEQ0g/JNPRu1fSkwDWE9E1AH4CMFbn43meDz9USz/vvltdj9lTL1DSqpXqzSJEQ0k/JNPRNTEw8wGouQbfZK9VSEhwb62CEO4i/ZBMyfQtMQxzZa1C8+ZGRySE9qQfkilJYtDD//2fan51+bJqhtWmjdERCaE96YdkWnI9Bq1dvKhOq48dAz75BOjc2eiIhNCe1aouHhUeDjz7rNHRCI1JYtCS1QqMHg3s3q0uuNG3r9ERCaEPez+k9eulH5IJyVCSlmbMAP7xD7U09YEHjI5GCH1IPyTTkzMGrSxbporXJkxQY65CmNW8eUBRkZo/89Tl18IlcsaghZwcdS1lT69VEMJVhw6py70+9phh1yMW+pMzBi106gRs3gwMGCC1CsK8mFWFc/PmwEsvGR2N0JEkBq3cc4/REQihL+mH5DNkKEkIUT/ph+RT5IzBSbm5ubBY3Nvto6ioCK08/JOap8aYm5trdAjeTfoh+RRJDE46ffq0249psViQnZ3t9uM2hDfEKBpI+iH5HBlKEkJcnfRD8jmSGIQQdZN+SD5JEoMXSUlJMTqEenlDjMJB0g/JZ8kcgxfxhj+63hCjcJD0Q/JZcsYghKhJ+iH5NDljEELUJP2QfJqcMXiY/Px83HbbbYiJiUG3bt2wZMmSGtvs2rULwcHBiIuLQ1xcHObNm+f2OKOionDjjTciLi6u1noOZsakSZMQHR2NHj16YP/+/W6PUThJ+iH5PDlj8DB+fn5YuHAh4uPjUVJSgoSEBAwcOBBdu3attl2/fv2wdetWg6JUdu7cidDQ0Fofy8jIQE5ODnJycpCZmYknnngCmZmZbo5QNJj0QxLQ+YyBiHKJ6DsiOkBEUvXkgLCwMMTbPqUFBgYiJiYGBQUFBkfVcFu2bMHo0aNBROjduzfOnj2LkydPGh2WqI+9H9ILL0g/JB/mjqGk25g5jpnd2z/CBHJzc/H111+jV69eNR7bs2cPYmNjMWTIEBw8eNDtsRERBg0ahISEBKSmptZ4vKCgAO3bt6/8PiIiwisTnE+RfkjCRoaSPFRpaSmSkpKwePFiBAUFVXssPj4ex44dQ0BAANLT03HvvfciJyfHrfHt3r0b4eHhOHXqFAYOHIguXbrg1ltvrXycmWs8h2QS07NJPyRho/cZAwPYTkT7iEgWuDuovLwcSUlJGDlyJEaMGFHj8aCgIATY1pUnJiaivLzc7b2bwsPDAQCtW7fG8OHDkZWVVe3xiIgI5OfnV35//PjxyucIDyT9kEQVeieGPswcD2AIgAlEdOuVGxBRChFlE1F2UVGRzuF4PmbGuHHjEBMTg6lTp9a6TWFhYeUn8qysLFitVoSEhLgtxvPnz6OkpKTy6+3bt6N79+7Vthk2bBjWrl0LZsbevXsRHByMsLAwt8UoGmjGDKC8HFi40OhIhAfQdSiJmU/Y/j1FRP8EcBOAz67YJhVAKgBYLJaa4w8+Zvfu3Vi3bl3lUlAAWLBgAfLy8gAA48ePR1paGlasWAE/Pz/4+/tj48aNbh2m+fnnnzF8+HAAwOXLl5GcnIzBgwdj5cqVlTEmJiYiPT0d0dHRaNasGVavXu22+EQD2fshzZoFXH+90dEID0C1jQVrsmOi5gAaMXOJ7esdAOYx80d1PcdisbC0bBbCjaxW4KabgJMngcOHpfWFyRHRPkcWAul5xtAGwD9tn2T9ALx3taQghDCAvR/Su+9KUhCVdEsMzPwTgFi99i+EcJG9H9IttwDJyUZHIzyILFcVwldJPyRRB+mVJIQvsvdDGjdO+iGJGiQxCOFrpB+SqIcMJQnha+z9kBYtAlq3Njoa4YHkjEEIXyL9kIQDJDEIfPXVV+jRowcuXryI8+fPo1u3bvj++++NDkvowd4PackS6Yck6qRbgZszpMDNOLNnz8bFixdx4cIFRERE4Fm5+Lv5nDgB3HADMGAA8MEHRkcjDOBogZskBgEAKCsrQ8+ePdG0aVN8+eWXaNy4sdEhCa2NGgW8/z7www/S+sJHOZoY6h1KIqKJRNRSm7CEpzpz5gxKS0tRUlKCixcvGh2O0Jq9H9Izz0hSEPVyZI6hLYCviOh9IhpM0lTflFJSUvDiiy9i5MiRmDFjhtHhCC1ZrcCTTwLh4YAMEQoH1JsYmHk2gE4A3gYwBkAOES0gIvnYYRJr166Fn58fkpOTMXPmTHz11Vf4z3/+Y3RYQiv2fkivvmr6fkj9+/fHqlWrKr8/deoUHnroIYSHhyM4OBh9+vSRa487wKFVSawmIgptt8sAWgJII6JXdYxNuMno0aOxefNmAEDjxo2RmZmJ22+/3eCohCZ8pB8SM8Nqtda4v7S0FD179sS+fftw5swZPPLIIxg6dChKS0sNiNKLMPNVbwAmAdgH4GMA9wNoYru/EYCj9T2/IbeEhAQWQmho6lRmIuZ9+4yOpE6RkZG8YMECjomJ4RYtWvCYMWP4woULfObMGR46dCiHhoZyixYteOjQoZyfn1/5vN///vc8a9YsvuWWW7hp06acnJzMjRo14muvvZabN2/OEyZMqPV4gYGBnJ2d7a6X51EAZLMDf4sdOWMIBTCCme9k5n8wc7ktoVgB3KVDrhJCaMGL+iGtX78eH3/8MY4ePYojR45g/vz5sFqtGDt2LI4dO4a8vDz4+/tj4sSJ1Z63bt06pKamoqSkBGvWrEG/fv2wbNkylJaWYtmyZTWOc+DAAZSVlSE6OtpdL80rOTLHMIeZj9Xx2CHtQxJCuMzL+iFNnDgR7du3x3XXXYfnnnsOGzZsQEhICJKSktCsWTMEBgbiueeew6efflrteWPGjEG3bt3g5+eHJvUU7BUXF2PUqFF4/vnnERwcrOfL8XrSK0kIM/Kyfkjt27ev/DoyMhInTpzAr7/+iilTpuCjjz7CL7/8AgAoKSlBRUVFZZ1N1eddzYULF3D33Xejd+/eUrzpAGmJIYTZeGE/pPz8/Mqv8/LyEB4ejoULF+Lw4cPIzMxEcXExPvtMXS6eqxTlXrl6vrbV9JcuXcK9996Ldu3a4a9//atOr8BcJDEIYTZe2A9p+fLlOH78OM6cOYMFCxbgwQcfRElJCfz9/dGiRQucOXMGc+fOrXc/bdq0wU8//VT5fXl5Oe677z74+/tj7dq1aNRI/uQ5Qv6XhDCTEyeA+fOBe+4BBg40OhqHJScnY9CgQejYsSM6duyI2bNn46mnnsKFCxcQGhqK3r17Y/DgwfXuZ/LkyUhLS0PLli0xadIkfPnll9i6dSu2b9+OFi1aICAgAAEBAfj888/d8Kq8l/RKEsJMvLAfUlRUFFatWoUBAwYYHYrpadYrSQjhJaQfktCI7omBiBoT0ddEtFXvYwnhs6QfktCQO5arTgZwCECQG44lhG+y90N6912v64eUm5trdAjiCrqeMRBRBIChAFbVt60wueJidRPa85F+SMJ99D5jWAxgOoBAnY8jPFVZGbB8OTB3LnDddWocvE0bo6Myl3nzgKIiICMDuEpX/NDQUERFRbkvLuGS3NxcnD592pBj65YYiOguAKeYeR8R9b/KdikAUgCgQ4cOeoUj3I1ZVd8+/TSQkwPccYdKCnffDezcqVo1CNc1oB9SVFQUZNWf97BY6l08pBs9h5L6ABhGRLkANgK4nYjevXIjZk5lZgszW1q1aqVjOMJtvv8euPNOYNgwoHFjID0d+OQTYMMGNQ7+0ENARYXRUXo/L+uHZEqnT6vlwR607F8LuiUGZn6WmSOYOQrAHwD8h5kf1ut4wgOcPg386U9AbCyQna0+yX77LTBkiHp82DB137/+BUyaZLo3k9vZ+yE+FLkaAAAa4UlEQVS98IJX9EMypbFjgQcfVMN5JiJN9ITrqs4jlJaq/jzPPw+EhNTcdsIE4Ngx4LXXgN/9Tq25Fw3nhf2QTCcjQyXn6GiVnCMjgTFjjI5KE24pcGPmXcws124wG2b16b97d2DqVODmm4HvvlNnBbUlBbtXXgEeeACYNk2dhotKhw8fRlxcXOUtKCgIixcvrrbNrl27EBwcjLijRxF36RLmvfyyQdH6sLIy4KmngBtuAA4cUO1HHn8c2LHD6Mg0IWcMwjnff6+SwY4dQJcuah7BPmRUn0aNgHfeUX19Ro0CwsKAfv30jddLdO7cGQcOHAAAVFRUoF27dhg+fHj1jU6fRr/Ll7H1nnuADz4wIEqBN98EjhwBtm1Tczxpaep3OCkJ+OILoEcPoyN0ibTEEA1T3zyCo5o2BbZsUcNJ99wDHD6sT7xe7N///jeuv/56REZGVn/gr39Vlc4LFxoTmK8rLFTDpkOHAomJ6r6gIJUkgoLUfcePGxujiyQxCMeUlal2ztHRQGqqGtfOyVFtGJxt7XzddepMo0kTlVh+/lnbmL3cxo0b8dBDD1W/c88e4JNPsKdpU8SOGIEhQ4bg4MGDde4jNTUVFosFFosFRUVFOkfsI2bNAi5eVO+HqiIi1O9zcbFKDufOGROfFhy5MLS7bgkJCa5f7Vpoy2pl/vBD5k6dmAHmwYOZf/hB22NkZTH7+zP37MlcWqrtvr3UpUuXOCQkhAsLC3+7s6KCOSGBz7VtyyUnTzIz87Zt2zg6Otqhfcr7SwOZmep9MG1a3dts387s58c8YABzWZnTh9Lj5wUgmx34WyxnDKJutdUjZGSolTBa6tkT2LhRahyqyMjIQHx8PNpUrRK39UMKev11BLRtCwBITExEeXm5YRWyPsVqVcus27YFZs+ue7uBA4G33lK1OykpXrksWxKDqEmreYSGkBqHajZs2FB9GKlKP6TC22+vvLxlVlYWrFYrQq62Ckxo4913gcxMtaouqJ6eoGPGqCWsa9Z4Z42DI6cV7rrJqa7BLl1ifuMN5uBg5saNmZ98kvn0affGMG2aOlV/7TX3HteDnD9/nq+77jo+e/Zs5X0r7riDVwDM+/bxm2++yV27duUePXpwr169ePfu3Q7tV95fLiguZm7blvmmm9SQniOsVuYxY9Tv8+rVDT6kkUNJhieDqjf5xTWIO+YRHFVRwfzAAyqOv//dmBg8zQ8/qDHrxx5zaTfy/nLB9OnqdzIzs2HPKytjHjhQ/fy2b2/QU2WOQRjHXfMIjrLXOPTtq2ocfP3avCz9kAyXk6NWII0ZA9x0U8Oe26SJqnHo2lXVOHz7rS4hak0Sg68yYh7BUVLj8Bvph2S8KVPU76SzFeZeWOMgicHX6FGPoAepcZB+SJ4gI0P9UZ8zR61GcpaX1ThIYvAV7GRfIyN17Kg+MRcWqus4nD9vdETutWgRcPQosGSJZyVtX1G1H9KkSa7vr0cPYNMmdQ2N++4Dystd36dOJDH4Ak+bR2gIX61xOHECmD9fDaUNHGh0NL5p6VLVD2nRIuCaa7TZp5fUOEhiMDNPnkdoCF+scZgxQ32ilH5IxigsVPUHVfshacULahyku6oZNeT6CN7Cl67jsGePKqaaNQu4/nqjo/FNzz5bez8krcyZA+Tmeux1HCQxmAlfcZ3lwYOBN97wjiEjR7zyikoO06YBHTqoazqYjdWqFgKEh6s/TsL9srLUp/lp04BOnfQ5BpFa/FFQoK7j0K6dRw0ZylCSWXjzPIKjfKHGwdYPCa++CgQEGB2N73G0H5IW7DUON9+s3rMeRBKDtzPLPIKjzFzjUKUfEpKTjY7GN61b53g/JC0EBQGffgrcfrv+x2oASQzeylvqEfRg1hqHefOAoiJ1dTAio6PxPSUlwMyZqrp51Cj3HdcDf9aSGLyNN9Yj6MFsNQ6HDqmf4bhxQHy80dH4pvnz1e/Tm2+qYUsf5tuv3tv4wjxCQ5ilxkH6IRnPXq/gTD8kE9ItMRBRUyLKIqJviOggEc3V61im52vzCA1hhhoH6YdkvKlTXeuHZDJ6Lle9BOB2Zi4loiYAviCiDGbeq+MxzcWM9Qh68OYahzr6IUVFRSEwMBCNGzeGn58fsrOzqz2NmTF58mSkp6ejWbNmWLNmDeJlCMo56emqH9Jrr7nWD8lEdEsMtt7fpbZvm9huXvhxziDp6eoPxpEj5qtH0IO31jjY+yFt315j0cDOnTsRGhpa69MyMjKQk5ODnJwcZGZm4oknnkBmZqY7IjaXsjL1PtOqH5JJ6DrHQESNiegAgFMAdjBzjd9cIkohomwiyi4qKtIzHO/xzjuqFL9RI5lHcJQ31ji40A9py5YtGD16NIgIvXv3xtmzZ3Hy5EmdAjUxPfohmYCuiYGZK5g5DkAEgJuIqHst26Qys4WZLa1atdIzHO/wySfAY48BAwYA33wj8wgN4W01Dlfph0REGDRoEBISEpCamlrj8YKCArRv377y+4iICBQUFNTYLjU1FRaLBRaLBfLB6wr2fkiJidr3Q/JyblmVxMxnAewCMNgdx/Na334LjBihzg7S0uQTjDO8pcbB3g/pmWdq7Ye0e/du7N+/HxkZGVi+fDk+++yzao9zLZPsVMt6+JSUFGRnZyM7OxvywesK9n5IixcbHYnH0XNVUisiamH72h/AAAA/6nU8r3f8uPrUEhSk/rAFBxsdkffy9BoHB/ohhYeHAwBat26N4cOHIysrq9rjERERyM/Pr/z++PHjlc8RDrD3Q5oyRb9+SF5MzzOGMAA7iehbAF9BzTFs1fF43qu4WM0pFBer1REREUZH5P08ucahnn5I58+fR0lJSeXX27dvR/fu1Udhhw0bhrVr14KZsXfvXgQHByMsLMwt4Xs9e2J2Rz8kL6XnqqRvAfyPXvs3jfJydTWnH35QSSE21uiIzMNe4zBxolpxsmyZW9sPLFu2DCNHjkTLli1/u9OBfkg///wzhg8fDgC4fPkykpOTMXjwYKxcuRIAMH78eCQmJiI9PR3R0dFo1qwZVq9erfvrMY116347YwgMNDoajyRtt43EDPzxj8COHcDf/gYMGmR0ROZjYI1DYWEhevbsifj4eDz66KO48847QfZ+SBkZdSapjh074ptvvqlx//jx4yu/JiIsX75ct9hNy94PqVcv9/ZD8jLSEsNIL76ohhWefx4YO9boaMzrlVdUXcO0acD777vtsPPnz0dOTg7GjRuHNWvWoFNkJGYtWoSj998v/ZCMYu+HtHSpz/dDuhr5nzHKO++ohPDII+pfoR8DaxyICG3btkXbNm3gd+YMfmnSBPf98AOmT5/uthiEjfRDcpgkBiNUrVVITfXItrumY0CNw9KlS5GQkIDp06ejT9Om+O78eaz4f/8P+775Bps2bdL9+B6PGbh82X3Hk35IDpPE4G5Sq2AcN9c4nD59Gps3b8bHH36I+zdtQhNbP6RGjRph61YfX6C3d69qGd++PfDf/+p/PHs/pDlzpB+SAyQxuJPUKhjPjTUO8+bNQ2Rk5G/9kJYsqeyHFOOrLU7y84GRI1VSyMtTq/KGDFEdhPUi/ZAaTBKDu0itgudwZ42DC/2QTOX8edVWvHNnYPNmVT9w5Ihql378uFpafOGCPse290NavFjO0B0kicEdqtYqpKVJrYIncNd1HK7SD8knWK3A+vUqIcydq/7ff/xRrcgLCFBnDu++q4aWHn5Y+yRt74c0dKj0HWsASQx6q1qrkJoqtQqeZMIEtYT1L3/R5w93Pf2QTG/vXlXI9/DDQFgY8MUX6kwtMrL6dklJqq385s3q56Elez+kRYu03a/ZMbPH3BISEth05s5lBpiff97oSERtKiqYH3hA/Yz+/ndt95uQwBwezlxSot1+XeC291deHnNysvo/DQtjXrNG/X/UZ/Jk9ZzFi7WJIzNT7W/6dG3252Z6/LwAZLMDf4sNTwZVb6ZLDGvWqP/iRx5htlqNjkbU5cIF5r59ma+5hvmzz7TZ56pV6mf/7rva7E8Dur+/SkvVByB/f+amTZlnz25YUrx8mXn4cGYi5s2bXYulooK5Vy/mtm2Zi4td25dBJDGYMTHs2MHs58c8YADzpUtGRyPq83//x9y5M3PLlsw//ujavs6eZW7dmvmWWzzqA4Fu76+KCpUA27VTf1IefJA5N9e5fZ0/z9y7t0ose/Y4H5P9Q9maNc7vw2BGJgaZY9CD1Cp4Hy1rHOz9kN580/zFi47OIziqWTPgww+Bdu3UcmJnahykH5LLJDFozV6rEBiolqVKrYL30KLG4dAhtdpp3Dhz90OqqABSUn6rR1izBsjMBPr0cX3frVqpJoPMztU4SD8kl8n/mpaq1iqkp6uqTuFdXKlxYFaFVM2bAy+9pF+MRrO/zrfeAp5+WtUIPPKItn+EO3VSZw75+Q2rccjJkX5IGpDEoBV7rcLBg1Kr4O2crXHYuhX4+GNVyNW6ta4hGmrxYjVMNnUq8PrrtV5sSBO33KJqIBpS4zBlivRD0oIjExHuunnt5LPVyjx2rJrsevtto6MRWpk2Tf1MX3ut/m0vXmS+/nrmmBjmsjKnD5mXl8f9+/fnLl26cNeuXXlxLUs3d+7cyUFBQRwbG8uxsbE8d+5ch/atyfvrH/9Qq4aSkhxbgqqFN95QP4cpU66+XXq64z8vLyCrkrw9MdhrFebMMToSoaWG1Di8/LLabvt2lw554sQJ3rdvHzMzFxcXc6dOnfjgwYPVttm5cycPHTq0wft2+f21ezfztdeq1Va//uravhrCamWeNImvWuNw6RLzDTeom0lWARqZGOQKbq6yX1dh9Gg1hCDMw34dhxMn1OqWsDCgX7+a22nYDyksLKzy2s2BgYGIiYlBQUEBunbt6tJ+XXbkiBpi69BBtS/393ffsYlUZXRenhoq6tABsF36tJK9H1J6uqwC1IDMMbjCfl2FO+5QE3FmX5roixy5joNO/ZByc3Px9ddfo1evXjUe27NnD2JjYzFkyBAcPHiwzn2kpqbCYrHAYrGgqKjIuUBOnVKrgxo1UquFQkOd248rGjdW8w033aSulb1372+PST8k7TlyWuGum1cNJX3zDXNgIHP37qqgSZjb0aOqaO13v2MuLPzt/i+/VEMcs2ZperiSkhKOj4/nTZs21Xjs3LlzXGKrKN62bRtHR0c7tE+n3l/nz6sKYn9/5r17G/58rZ06peZyQkOZc3LUfWPHMjdpwnzkiLGxacyUBW5E1J6IdhLRISI6SEST9TqW21WtVZDrKviG2mocrFbgySeB8HDVrE0j5eXlSEpKwsiRIzFixIgajwcFBSHAthIoMTER5eXlOK3H9QwqKtS1E7KygPfeUwVjRmvVSr3n2FbjkJ6urps+ZYpa4io0oedQ0mUATzNzDIDeACYQkcEDpRqQWgXfdWWNw6pV6utXX9VsySYzY9y4cYiJicHUqVNr3aawsFCtHAGQlZUFq9WKkJAQTY5fJRD1x/aDD9QFhu69V9v9u+KGG36rcRg6VF2RbfZso6MyFd0mn5n5JICTtq9LiOgQgHYAftDrmLqrWquQni61Cr7IXuMwcaI6g7jlFjXmrZHdu3dj3bp1uPHGGxEXFwcAWLBgAfLy8gAA48ePR1paGlasWAE/Pz/4+/tj48aNIK3nt6rWKjz5pLb71oK9xiE5Wc3tBAYaHZG5ODLe5OoNQBSAPABBtTyWAiAbQHaHDh00H1PTjNQqiKpmzFBLN7OzjY7EYQ6PWRtRq+Asdy6bdTNTzjHYEVEAgE0AnmLm4loSUyozW5jZ0qpVK73Dcd6LL6qxzDlzgEcfNToaYbRXXlGN8hISjI5EW19+qaqMb74ZWLfO83sNuXPZrA/R9adORE2gksJ6Zt6s57F0JbUKojZmG74wslZBeBQ9VyURgLcBHGLmN/Q6ju6kVkH4Ak+oVRAeQ88zhj4ARgG4nYgO2G6JOh5Pe/brKnTpAmzaJBWVwpx+/VWdKZw8qRoH+uL1qUU1eq5K+gKA9368lloF4Quq1ips3uwZtQrCcNIrqTZVaxU+/1xqFYQ5Va1VWLrUs2oVhKEkMVxJahWEr/D0WgVhGEkMVTEDf/wjsGMH8PbbwKBBRkckhD4yMtTV15KSgNdeMzoa4WE8fJGym0mtgvAVffoAzzzjHbUKwu3kjMFOahWELwkKUj2ehKiFfFQApFZBCCGqkDMGqVUQPiI3NxcWi8WtxywqKoJHt7qB58aYm5tr2LF9OzEUFEitgvAZulyzoR4WiwXZ2dluP25DeEOM7ua7iUFqFYQQola+mRjKy4H77we+/15qFYQQ4gq+lxiYgfHjge3bpVZBCJ2lpKQYHUK9vCFGdyO2XSLQE1gsFtZ9rO/FF1Wdwpw5wNy5+h5LCCE8CBHtY+Z6VyD41nLVd95RCUFqFYQQok6+kxj+/W+pVRBCCAf4RmL47jupVRBCJ/n5+bjtttsQExODbt26YcmSJTW22bVrF4KDgxEXF4e4uDjMmzfP7XFGRUXhxhtvRFxcXK31HMyMSZMmITo6Gj169MD+/fvdHqOnMP/ks71WISBAahWE0IGfnx8WLlyI+Ph4lJSUICEhAQMHDkTXrl2rbdevXz9s3brVoCiVnTt3IrSOq9NlZGQgJycHOTk5yMzMxBNPPIHMzEw3R+gZzH3GYK9VOHdOJQWpVRBCc2FhYYiPjwcABAYGIiYmBgUFBQZH1XBbtmzB6NGjQUTo3bs3zp49i5MnTxodliHMmxiq1iqkpUmtghBukJubi6+//hq9arkS3J49exAbG4shQ4bg4MGDbo+NiDBo0CAkJCQgNTW1xuMFBQVoX+XDY0REhFcmOC2YcyhJahWEcLvS0lIkJSVh8eLFCAoKqvZYfHw8jh07hoCAAKSnp+Pee+9FTk6OW+PbvXs3wsPDcerUKQwcOBBdunTBrbfeWvl4bUv3yUcXqZjzjGH+fOBvf5PrKgjhJuXl5UhKSsLIkSMxYsSIGo8HBQUhICAAAJCYmIjy8nK3924KDw8HALRu3RrDhw9HVlZWtccjIiKQn59f+f3x48crn+NrzJcYpFZBCLdiZowbNw4xMTGYOnVqrdsUFhZWfiLPysqC1WpFSEiI22I8f/48SkpKKr/evn07unfvXm2bYcOGYe3atWBm7N27F8HBwQgLC3NbjJ5Et6EkIvobgLsAnGLm7vVtrwmpVRDC7Xbv3o1169ZVLgUFgAULFiAvLw8AMH78eKSlpWHFihXw8/ODv78/Nm7c6NZhmp9//hnDhw8HAFy+fBnJyckYPHgwVq5cWRljYmIi0tPTER0djWbNmmH16tVui8/T6NYSg4huBVAKYK2jicGllhjffQf07Qt06AB88YUsSxVCiCsY3hKDmT8DcEav/VcjtQpCCKEZw1clEVEKgBQA6NChg3M7eestVasg11UQQgiXGT75zMypzGxhZovTl9d7/nkgO1tqFYQQQgOGJwZNEAE33GB0FEIIYQrmSAxCCCE0o1tiIKINAPYA6ExEx4lonF7HEkIIoR3dJp+Z+SG99i2EEEI/MpQkhPA6X331FXr06IGLFy/i/Pnz6NatG77//nujwzINw5erCiFEQ/Xs2RPDhg3D7NmzceHCBTz88MM1WlwI5+lW+ewMlyqfhRA+paysDD179kTTpk3x5ZdfonHjxkaH5PEMr3wWQgg9nTlzBqWlpSgpKcHFixeNDsdUJDEIIbxSSkoKXnzxRYwcORIzZswwOhxT8aihJCIqAnDMyaeHAnBvg3f9me01yevxfN7ymkIAtABw1PZ9FwAFAEqu2M5bXo+jXH09kcxcb4sJj0oMriCibEfGzryJ2V6TvB7PZ7bXJK/HOTKUJIQQohpJDEIIIaoxU2JINToAHZjtNcnr8Xxme03yepxgmjkGIYQQ2jDTGYMQQggNSGIQQghRjdcnBiL6GxGdIiJTdNAiovZEtJOIDhHRQSKabHRMriKipkSURUTf2F7TXKNj0gIRNSair4loq9GxuIqIconoOyI6QESm6EtDRC2IKI2IfrS9n242OiZnEVFn28/Gfismoqd0O563zzEQ0a0ASgGsZWav76JFRGEAwph5PxEFAtgH4F5m/sHg0JxGRASgOTOXElETAF8AmMzMew0OzSVENBWABUAQM99ldDyuIKJcABZmNk0xGBG9A+BzZl5FRNcAaMbMZ42Oy1VE1BiqmK8XMztbEHxVXn/GwMyfAThjdBxaYeaTzLzf9nUJgEMA2hkblWtYKbV928R28+pPJEQUAWAogFVGxyJqIqIgALcCeBsAmLnMDEnB5g4AR/VKCoAJEoOZEVEUgP8BkGlsJK6zDbscAHAKwA5m9vbXtBjAdABWowPRCAPYTkT7iCjF6GA00BFAEYDVtuG+VUTU3OigNPIHABv0PIAkBg9FRAEANgF4ipmLjY7HVcxcwcxxACIA3EREXjvsR0R3ATjFzPuMjkVDfZg5HsAQABNsQ7TezA9APIAVzPw/AM4DmGlsSK6zDYkNA/APPY8jicED2cbhNwFYz8ybjY5HS7bT+V0ABhsciiv6ABhmG5ffCOB2InrX2JBcw8wnbP+eAvBPADcZG5HLjgM4XuXMNA0qUXi7IQD2M/PPeh5EEoOHsU3Uvg3gEDO/YXQ8WiCiVkTUwva1P4ABAH40NirnMfOzzBzBzFFQp/X/YeaHDQ7LaUTU3LbQAbbhlkEAvHqVHzMXAsgnos62u+4A4LULOKp4CDoPIwEmuLQnEW0A0B9AKBEdB/A8M79tbFQu6QNgFIDvbGPyADCLmdMNjMlVYQDesa2maATgfWb2+iWeJtIGwD/VZxL4AXiPmT8yNiRNPAlgvW345ScAYw2OxyVE1AzAQAB/1P1Y3r5cVQghhLZkKEkIIUQ1khiEEEJUI4lBCCFENZIYhBBCVCOJQQghRDWSGIQQQlQjiUEIIUQ1khiEaCAi6klE39quM9Hcdo0Jr+39JMSVpMBNCCcQ0XwATQH4Q/XkedngkITQjCQGIZxga7PwFYCLAG5h5gqDQxJCMzKUJIRzrgMQACAQ6sxBCNOQMwYhnEBEH0K13P4d1KVYJxockhCa8fruqkK4GxGNBnCZmd+zdYz9kohuZ+b/GB2bEFqQMwYhhBDVyByDEEKIaiQxCCGEqEYSgxBCiGokMQghhKhGEoMQQohqJDEIIYSoRhKDEEKIav4/BTyTauuppUcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 定义figure\n",
    "fig = plt.figure()\n",
    "\n",
    "# 定义数据\n",
    "x = [1, 2, 3, 4, 5, 6, 7]\n",
    "y = [1, 3, 4, 2, 5, 8, 6]\n",
    "\n",
    "# figure的百分比, 从figure 10%的位置开始绘制, 宽高是figure的80%\n",
    "left, bottom, width, height = 0.1, 0.1, 0.8, 0.8\n",
    "# 获得绘制的句柄\n",
    "ax1 = fig.add_axes([left, bottom, width, height])\n",
    "# 绘制点(x,y)\n",
    "ax1.plot(x, y, 'r')\n",
    "ax1.set_xlabel('x')\n",
    "ax1.set_ylabel('y')\n",
    "ax1.set_title('test')\n",
    "\n",
    "\n",
    "# 嵌套方法一\n",
    "# figure的百分比, 从figure 10%的位置开始绘制, 宽高是figure的80%\n",
    "left, bottom, width, height = 0.2, 0.6, 0.25, 0.25\n",
    "# 获得绘制的句柄\n",
    "ax2 = fig.add_axes([left, bottom, width, height])\n",
    "# 绘制点(x,y)\n",
    "ax2.plot(x, y, 'r')\n",
    "ax2.set_xlabel('x')\n",
    "ax2.set_ylabel('y')\n",
    "ax2.set_title('part1')\n",
    "\n",
    "\n",
    "# 嵌套方法二\n",
    "plt.axes([bottom, left, width, height])\n",
    "plt.plot(x, y, 'r')\n",
    "plt.xlabel('x')\n",
    "plt.ylabel('y')\n",
    "plt.title('part2')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## matplotlib模块数据可视化-多图布局，分格显示\n",
    "### 通过subplot2grid实现"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plt.figure()\n",
    "# 通过栅格的形式创建布局方式,(3,3)创建3x3的布局形式，(0,0)绘制的位置，0行0列的位置绘制\n",
    "# colspan:表示跨几列 rowspan:表示跨几行\n",
    "ax1 = plt.subplot2grid((3, 3), (0, 0), colspan=3)\n",
    "# 在ax1图中绘制一条坐标(1,1)到坐标(2,2)的线段\n",
    "ax1.plot([1, 2], [1, 2])\n",
    "# 设置ax1的标题  现在xlim、ylim、xlabel、ylabel等所有属性现在只能通过set_属性名的方法设置\n",
    "ax1.set_title('ax1_title')  # 设置小图的标题\n",
    " \n",
    "ax2 = plt.subplot2grid((3, 3), (1, 0), colspan=2)\n",
    "ax3 = plt.subplot2grid((3, 3), (1, 2), rowspan=2)\n",
    "ax4 = plt.subplot2grid((3, 3), (2, 0))\n",
    "ax5 = plt.subplot2grid((3, 3), (2, 1))\n",
    "# 给对应的图绘制内容，这里只给ax4图绘制，属性通过set_xxx的模式设置\n",
    "ax4.scatter([1, 2], [2, 2])\n",
    "ax4.set_xlabel('ax4_x')\n",
    "ax4.set_ylabel('ax4_y')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 通过gridspec实现"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.gridspec as gridspec\n",
    "\n",
    "plt.figure()\n",
    "# 将整个视图分成3x3布局\n",
    "gs = gridspec.GridSpec(3, 3)\n",
    "# gs[0,:]  指定画图的位置 前面指定该图所占的行范围0表示0行，1: 表示从第一行到最后一行\n",
    "# 第二个参数指定列的范围一个数表示固定列数，x:y表示从x列到y列\n",
    "ax6 = plt.subplot(gs[0, :])\n",
    "ax6.plot((0,1),(0,1))\n",
    "# 第一行，从0列开始到2列，不包括2，也就是占0、1两列\n",
    "ax7 = plt.subplot(gs[1, :2])\n",
    "# 从第一行到最后，占1、2两行，后面的2表示只占用第二列，也就是最后的一列\n",
    "ax8 = plt.subplot(gs[1:, 2])\n",
    "# 倒数第一行，只占第0列这一列\n",
    "ax9 = plt.subplot(gs[-1, 0])\n",
    "# 倒数第一行，只占倒数第二列，由于总共三列，所以倒数第二列就是序号1的列\n",
    "ax10 = plt.subplot(gs[-1, -2])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 通过subplots实现"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 这种方法只适合列数相同的布局\n",
    "# sharex:所有小图共享x轴  sharey:表示所有小图共享y轴  坐标轴以所有小图中范围最大的进行显示\n",
    "f, ((ax11, ax12), (ax13, ax14)) = plt.subplots(2, 2, sharex=True, sharey=True)\n",
    "ax11.scatter([1,2], [1,2])\n",
    "ax12.plot((1,4),(1,4))\n",
    "# 紧凑显示，边框会比较小，可以注释掉该行查看效果\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "z"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
